Power optimization method of wind turbine generator

Abstract

The invention discloses a power optimization method for a wind turbine generator, relates to the technical field of wind turbine generators, and aims to further improve the conversion efficiency of wind energy through dynamic adjustment and optimization of a sharp speed ratio. By calculating the tip speed ratio under different wind speed conditions and combining the change range of the angular speed of the rotor, the relative optimal interval of the tip speed ratio is accurately obtained, the mechanical energy conversion efficiency of the wind wheel is monitored and evaluated, the wind wheel power coefficients under different wind speed conditions are calculated, and it is ensured that good power output can be achieved under various wind speed conditions. And finally, the feedback regulation of the rotor angular speed further smooths the output power. After the standard conversion conditions are obtained, the system can trace and adjust the angular speed of the rotor, so that the wind turbine generator can adapt to different wind speed changes, and stable power output is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of wind turbine generator sets, and in particular to a power optimization method for wind turbine generator sets. Background Art

[0002] Wind turbines are key equipment for converting wind energy into electrical energy. Their working efficiency and operating stability are crucial to the power generation capacity of the entire wind farm and the stability of the power grid. In practical applications, wind turbines will be affected by wind speed fluctuations, resulting in instability in output power, which in turn causes fluctuations in the power supply of the power grid. This power fluctuation will not only affect the safe operation of the power grid, but may also cause a decrease in the working efficiency of wind turbines and increased equipment fatigue. In order to improve power generation efficiency and ensure the stability of the power grid, it is necessary to study how to monitor the key parameters of wind turbines to optimize their operating strategies, effectively reduce power output fluctuations, and achieve smooth power output. This leads to the need for smooth optimization of wind turbine power. In order to solve these problems, a power optimization method for wind turbines is proposed.

[0003] The above problems are related to the uncontrollability of wind speed and the complexity of the internal system of wind turbines. In actual operation, wind speed changes frequently and is difficult to predict, which directly affects the speed and power output of the wind rotor. However, most existing wind turbine control methods rely on a single speed feedback, which makes it difficult to achieve dynamic response under multivariable conditions. When the power output is unstable, a series of abnormal effects will be triggered, such as power fluctuations leading to instability of grid frequency and voltage, which may cause grid overload or insufficient power supply. Especially when the wind speed changes sharply, the inertia of the rotor is difficult to fully absorb and buffer such fluctuations, resulting in unstable power output; in addition, the real-time monitoring and control of power output lags, making it difficult to quickly adjust and optimize. At the same time, since the equipment is frequently in a state of power fluctuation, mechanical components, especially rotors and blades, will suffer greater mechanical stress, resulting in premature fatigue of the equipment and increased maintenance and operating costs. Therefore, power output fluctuations not only affect the stability of the power grid, but also bring additional operation and maintenance burdens. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a power optimization method for a wind turbine generator set, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A power optimization method for a wind turbine generator system comprises the following steps:

[0006] S1. Deploy several groups of monitoring equipment in the wind farm in advance, and use the monitoring equipment to monitor and record relevant power output data information and relevant rotor status data information in the wind turbine in real time;

[0007] S2, preprocessing the relevant power output data information and the relevant rotor status data information to generate a wind turbine operation data set, and using dimensionless technology to standardize the information in the wind turbine operation data set;

[0008] S3. Based on the relevant power output data information, the power output difference coefficient Scxs under different wind speed conditions is analyzed and calculated, and the power output difference coefficient Scxs is compared and analyzed with the preset safety range [a, b] to preliminarily screen out the matching range of rotor kinetic energy absorption;

[0009] S4. Based on the initially selected matching range of rotor kinetic energy absorption, determine the range of rotor angular velocity Jsd, and calculate the tip speed ratio Jsb under different wind speed conditions according to the ratio of the speed of the tip of the wind rotor blade to the corresponding wind speed, and obtain the tip speed ratio Jsb range in combination with the range of rotor angular velocity Jsd;

[0010] S5. Based on the tip speed ratio Jsb range obtained in S4, monitor the efficiency of the wind rotor in converting wind energy into mechanical energy under the corresponding wind speed conditions within the tip speed ratio Jsb range to obtain relevant energy conversion data information, and calculate the wind rotor power coefficient Fgxs under the corresponding wind speed conditions based on the relevant energy conversion data information, and extract the standard conversion conditions through feature extraction;

[0011] S6. Based on the standard conversion condition, trace back and adjust the rotor angular velocity Jsd to smooth the output power of the wind turbine.

[0012] Preferably, the specific steps of S1 include:

[0013] S11. deploying several groups of monitoring equipment in the wind farm in advance, wherein the several groups of monitoring equipment include power sensors, strain gauges, laser rangefinders, rotation speed sensors, wind speed sensors, and torque sensors;

[0014] S12, using the monitoring equipment in S11 to monitor and record relevant power output data information and relevant rotor status data information in the wind turbine in real time, wherein the relevant power output data information includes the output power value Scg under various wind speed conditions;

[0015] The relevant rotor state data information includes the mass Zg of each divided area of ​​the rotor, the distance Jz of each divided area from the rotation axis, and the angular velocity Jsd of the rotor.

[0016] Preferably, the specific steps of S2 include:

[0017] S21, pre-processing the relevant power output data information and the relevant rotor state data information to identify and remove abnormal values ​​in the relevant power output data information and the relevant rotor state data information, and fill in the missing data using an interpolation method, and at the same time, time-aligning the relevant power output data information and the relevant rotor state data information, and finally generating a wind power operation data set;

[0018] S22. By using dimensionless processing technology, the information in the wind power operation data set is converted into unitless data through dimensionless processing technology, and the dimensionless wind power operation data set is standardized so that the corresponding data values ​​are mapped to the interval [0,1].

[0019] Preferably, the specific steps of S3 include:

[0020] S31. Based on the relevant power output data information, the power output difference coefficient Scxs under different wind speed conditions is analyzed and calculated, which is obtained in the following way:

[0021]

[0022] Where n represents the number of monitored wind speed conditions, i = 1, 2, 3, ..., n, Scg i It is expressed as the output power value under wind speed condition i, Scg avg Expressed as average output power value.

[0023] Preferably, the specific step S3 also includes:

[0024] S32, pre-set the safety range [a, b], and compare and analyze it with the power output difference coefficient Scxs under various wind speed conditions to preliminarily screen out the matching range of rotor kinetic energy absorption. The specific judgment content is as follows:

[0025] S321, if the power output difference coefficient Scxs does not fall within the safety range [a, b], the relevant rotor status data information under the corresponding wind speed conditions will not be extracted and analyzed at this time;

[0026] S322, if the power output difference coefficient Scxs falls within the safety range [a, b], then relevant rotor status data information under corresponding wind speed conditions will be extracted and analyzed;

[0027] S33, statistically analyzing the relevant rotor state data information under the corresponding wind speed conditions extracted in S322 to construct a conditional data group, and analyzing and calculating the rotor kinetic energy Znn under the corresponding wind speed conditions based on the conditional data group, wherein the rotor kinetic energy Znn is specifically obtained in the following manner:

[0028]

[0029] Where m is the number of regions into which the rotor is divided, j = 1, 2, 3, ..., m, Zg j Expressed as the mass of the rotor in the jth region, Jz j It is represented as the distance of the jth region from the rotation axis, Jsd is represented as the angular velocity of the rotor, Expressed as rotor inertia;

[0030] S34, statistically analyzing the rotor kinetic energy Znn under the corresponding wind speed conditions obtained in S33 to determine the range of rotor kinetic energy absorption under the wind speed conditions corresponding to the power output difference coefficient Scxs.

[0031] Preferably, the specific steps of S4 include:

[0032] S41, based on the preliminary screening of the matching range of rotor kinetic energy absorption, and combined with the method of obtaining the rotor kinetic energy Znn, to determine the range of the rotor angular velocity Jsd;

[0033] S42, according to the ratio of the speed of the tip of the wind rotor blade to the corresponding wind speed, calculate the tip speed ratio Jsb under different wind speed conditions, which is specifically obtained in the following manner:

[0034]

[0035] Where Bjz represents the radius of the wind wheel, Jsd represents the angular velocity of the rotor, and Fs represents the wind speed.

[0036] Preferably, the specific step S4 also includes:

[0037] S43. Based on the range of the rotor angular velocity Jsd and in combination with the tip speed ratio Jsb under different wind speed conditions obtained in S42, obtain the range of the tip speed ratio Jsb.

[0038] Preferably, the specific steps of S5 include:

[0039] S51, based on the tip speed ratio Jsb range obtained in S43, monitoring the efficiency of the wind rotor in converting wind energy into mechanical energy under the corresponding wind speed conditions within the tip speed ratio Jsb range, so as to obtain relevant energy conversion data information, wherein the relevant energy conversion data information includes the mechanical power value P generated by the wind rotor under each wind speed condition mechanical and the wind energy P captured by the wind rotor wind .

[0040] Preferably, the specific step S5 also includes:

[0041] S52. Based on the relevant energy conversion data information, the wind rotor power coefficient Fgxs under the corresponding wind speed condition is calculated. The wind rotor power coefficient Fgxs under the corresponding wind speed condition is obtained in the following manner:

[0042]

[0043] Where P mechanical is the mechanical power value generated by the wind wheel, P wind Expressed as the wind energy captured by the wind rotor. Among them, π*Bjz 2 is the area swept by the wind wheel; ρ is the air density; π is the circumference of a circle;

[0044] S53. Based on the method of obtaining the wind rotor power coefficient Fgxs in S52, the wind rotor power coefficient Fgxs under each wind speed condition is calculated respectively. After feature extraction, the maximum value of the wind rotor power coefficient Fgxs is extracted, and the maximum value of the wind rotor power coefficient Fgxs is used as the standard conversion condition.

[0045] Preferably, the specific step S6 includes:

[0046] S61. Based on the standard conversion conditions, trace back the wind speed conditions corresponding to the standard conversion conditions, and trace back to the corresponding tip speed ratio Jsb according to the wind speed conditions, and extract the angular velocity Jsd of the rotor under the corresponding wind speed conditions from the range of the angular velocity Jsd of the rotor according to the tip speed ratio Jsb under the wind speed conditions, and adjust the angular velocity Jsd of the rotor in the wind turbine according to the value of the angular velocity Jsd of the rotor to smooth the output power of the wind turbine.

[0047] The present invention provides a power optimization method for a wind turbine generator set, which has the following beneficial effects:

[0048] (1) First, the combination of real-time monitoring and data processing improves the system's ability to perceive the operating status of wind turbines. Through pre-deployed monitoring equipment, the power output and rotor status data of the wind turbine can be recorded in real time. Secondly, the calculation and analysis of the power output difference coefficient can dynamically identify the power output fluctuation under different wind speed conditions. By calculating the power output difference coefficient and comparing it with the preset safety range, a relatively suitable rotor kinetic energy absorption range can be preliminarily screened out, so that mechanical kinetic energy can be effectively absorbed when the wind speed fluctuates greatly, the fluctuation amplitude of the output power can be reduced, and the safe and stable operation of the system can be ensured. Third, the dynamic adjustment and optimization of the tip speed ratio further improves the conversion efficiency of wind energy. By calculating the tip speed ratio under different wind speed conditions and combining the variation range of the rotor angular velocity, the relatively optimal range of the tip speed ratio can be accurately obtained, and the mechanical energy conversion efficiency of the wind rotor can be monitored and evaluated, and the wind rotor power coefficient under different wind speed conditions can be calculated to ensure that the best power output can be achieved under various wind speed conditions. Finally, the feedback adjustment of the rotor angular velocity further smoothes the output power. After obtaining the standard conversion conditions, the system can trace back and adjust the angular velocity of the rotor, so that the wind turbine can adapt to different wind speed changes and achieve stable power output. This feedback adjustment mechanism effectively reduces the negative impact of wind speed fluctuations on power output and improves the operating efficiency and stability of the entire wind turbine. Therefore, through the coordinated work of the above steps, this method can further improve the power output stability of the wind turbine, reduce the impact of wind speed fluctuations on the power grid, and optimize the utilization efficiency of wind energy, thereby achieving safe, efficient and stable operation of wind power generation.

[0049] (2) By calculating the power output difference coefficient Scxs, the power output fluctuation of the generator set can be accurately evaluated under different wind speed conditions. This step dynamically calculates the difference coefficient based on the deviation between the actual power output and the average power under each wind speed condition, reflecting the output fluctuation of the system under different wind speed conditions. In this way, the system can understand the stability of the power output in real time and judge whether the system is within the safe range through the calculated difference coefficient.

[0050] (3) Based on the screening and data analysis of the safety range, the accuracy of data processing is further improved. By comparing and analyzing the calculated power output difference coefficient Scxs with the preset safety range, when the difference coefficient falls into the safety range, the system will extract and analyze the relevant rotor state data, screen out a more suitable rotor kinetic energy absorption range, and then optimize the adjustment of the rotor angular velocity and tip speed ratio, and reduce errors and interference. On this basis, by monitoring the energy conversion efficiency under different wind speed conditions, the system can calculate and extract the maximum value of the wind wheel power coefficient, and use it as the standard conversion condition to achieve precise adjustment of the rotor angular velocity. Through these steps, the system can achieve better power output and smooth operation under different wind speed conditions, reduce the impact of wind speed fluctuations on the power grid, and improve the utilization efficiency of wind energy. Compared with existing technical means, this method can better cope with wind speed changes through fine power difference analysis, precise matching and real-time adjustment of rotor kinetic energy absorption, and further improve the stability of power output and power generation efficiency. This method not only improves the overall operating stability of the wind turbine, but also extends the service life of the equipment by reducing power fluctuations and energy waste, thereby improving the economy and safety of the wind power generation system. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 The figure is a schematic flow chart of the power optimization method of the wind turbine generator set of the present invention. DETAILED DESCRIPTION

[0052] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] Example 1

[0054] See also Figure 1 The present invention provides a method for optimizing the power of a wind turbine generator system, comprising the following steps:

[0055] S1. Deploy several groups of monitoring equipment in the wind farm in advance, and use the monitoring equipment to monitor and record relevant power output data information and relevant rotor status data information in the wind turbine in real time;

[0056] S2. Preprocessing the relevant power output data information and the relevant rotor status data information to generate a wind power operation data set, and using dimensionless technology to standardize the information in the wind power operation data set;

[0057] S3. Based on the relevant power output data information, the power output difference coefficient Scxs under different wind speed conditions is analyzed and calculated, and the power output difference coefficient Scxs is compared and analyzed with the preset safety range [a, b] to preliminarily screen out the matching range of rotor kinetic energy absorption;

[0058] S4. Based on the initially selected matching range of rotor kinetic energy absorption, determine the range of rotor angular velocity Jsd, and calculate the tip speed ratio Jsb under different wind speed conditions according to the ratio of the speed of the tip of the wind rotor blade to the corresponding wind speed, and obtain the tip speed ratio Jsb range in combination with the range of rotor angular velocity Jsd;

[0059] S5. Based on the tip speed ratio Jsb range obtained in S4, monitor the efficiency of the wind rotor in converting wind energy into mechanical energy under the corresponding wind speed conditions within the tip speed ratio Jsb range to obtain relevant energy conversion data information, and calculate the wind rotor power coefficient Fgxs under the corresponding wind speed conditions based on the relevant energy conversion data information, and extract the standard conversion conditions through feature extraction;

[0060] S6. Based on the standard conversion condition, trace back and adjust the rotor angular velocity Jsd to smooth the output power of the wind turbine.

[0061] In this embodiment, firstly, by deploying monitoring equipment in the wind farm, the power output and rotor status data of the wind turbine are collected in real time, and combined with data preprocessing and dimensionless technology, the standardized processing of the data is ensured, so that the data under different wind speed conditions are more unified and comparable, which is convenient for subsequent analysis. Secondly, by analyzing the power output difference coefficient under different wind speed conditions and comparing it with the preset safety range, the relatively optimal range of rotor kinetic energy absorption can be screened out, further laying the foundation for the adjustment of the rotor angular velocity. On this basis, based on the calculation of the tip speed ratio and the determination of the rotor angular velocity, preparations are made to ensure that the rotor can always work within a relatively optimal range under different wind speed conditions. Subsequently, the system monitors the wind energy conversion efficiency under these conditions, and by extracting characteristic parameters and calculating the corresponding wind wheel power coefficient, the wind energy utilization efficiency under different wind speeds is optimized, and the energy capture efficiency of the wind wheel is improved as much as possible. Finally, by adjusting the rotor angular velocity based on the standard conversion conditions, this method can effectively smooth the output power of the wind turbine, reduce the power fluctuation caused by wind speed fluctuations, and ensure a more stable output power. This optimization method not only improves the efficiency of wind energy utilization through multiple data analysis and real-time adjustment, but also reduces power fluctuations during system operation, extends the service life of the equipment, and reduces the impact on the power grid, thereby achieving efficient, safe, and stable power generation.

[0062] Example 2

[0063] Please refer to Figure 1, specifically: S1 specific steps include:

[0064] S11. deploying several groups of monitoring equipment in the wind farm in advance, wherein the several groups of monitoring equipment include power sensors, strain gauges, laser rangefinders, rotation speed sensors, wind speed sensors, and torque sensors;

[0065] S12, using the monitoring equipment in S11 to monitor and record relevant power output data information and relevant rotor status data information in the wind turbine in real time, wherein the relevant power output data information includes the output power value Scg under various wind speed conditions;

[0066] The relevant rotor state data information includes the mass Zg of each divided area of ​​the rotor, the distance Jz of each divided area from the rotation axis, and the angular velocity Jsd of the rotor.

[0067] The specific steps of S2 include:

[0068] S21, pre-processing the relevant power output data information and the relevant rotor state data information to identify and remove abnormal values ​​in the relevant power output data information and the relevant rotor state data information, and using interpolation methods (such as linear interpolation, spline interpolation, etc.) to fill in the missing data, and at the same time, time-aligning the relevant power output data information and the relevant rotor state data information to ensure that the data has a consistent time dimension. This operation is usually called data synchronization, and finally generating a wind power operation data set;

[0069] S22. Through dimensionless processing technology, the information in the wind power operation data set is converted into unitless data through dimensionless technology for unified analysis. The dimensionless wind power operation data set is standardized so that the corresponding data values ​​are mapped to the interval [0,1] and the scale is unified. In this way, the operating status of the wind power generation system can be separated from the specific physical units and can be uniformly analyzed and compared.

[0070] In this embodiment, firstly, by deploying several groups of monitoring equipment in the wind farm, the power output data information of the wind turbine under different wind speed conditions and the detailed status data information of the rotor, such as the mass of each area of ​​the rotor, the distance from the rotating axis and the angular velocity of the rotor, can be accurately recorded. Through this high-precision monitoring, the comprehensiveness and accuracy of the data can be ensured, and high-quality input data can be provided for the subsequent optimization process. Secondly, data preprocessing and synchronization processing can effectively improve the quality of the data. Through the identification and elimination of outliers, the system can eliminate the interference caused by noise and abnormal data. At the same time, the interpolation method is used to reasonably fill the missing data to ensure the integrity and continuity of the data. The time alignment operation of the data can ensure that various types of data are compared and analyzed in the same time dimension, eliminating the errors caused by the acquisition time difference. This preprocessing further improves the accuracy and reliability of data analysis. Finally, dimensionless and standardized processing converts the data into a unitless form, further avoiding the unit and magnitude differences between different physical quantities, so that various types of data are analyzed under a unified scale. After dimensionless processing, the data is standardized so that the data is mapped to a unified interval for further comparison and processing. This processing not only simplifies the data analysis process, but also improves the stability of data processing and control algorithms, making the system optimization process more efficient and more robust. Therefore, through comprehensive collection, preprocessing, dimensionless processing and standardization of monitoring data, this method can significantly improve the quality and consistency of data, ensure that the power optimization process is more accurate and efficient, and thus achieve better power output smoothing effect and system stability.

[0071] Example 3

[0072] Please refer to Figure 1 , specifically: S3 specific steps include:

[0073] S31. Based on the relevant power output data information, the power output difference coefficient Scxs under different wind speed conditions is analyzed and calculated, which is obtained in the following way:

[0074]

[0075] Where n represents the number of monitored wind speed conditions, i = 1, 2, 3, ..., n, Scg i It is expressed as the output power value under wind speed condition i, Scg avg Expressed as average output power value.

[0076] The above output power value Scg is monitored and obtained through a power sensor or an electric energy meter;

[0077] The specific steps of S3 also include:

[0078] S32, pre-set the safety range [a, b], and compare and analyze it with the power output difference coefficient Scxs under various wind speed conditions to preliminarily screen out the matching range of rotor kinetic energy absorption. The specific judgment content is as follows:

[0079] S321, if the power output difference coefficient Scxs does not fall within the safety range [a, b], the relevant rotor status data information under the corresponding wind speed conditions will not be extracted and analyzed at this time;

[0080] S322, if the power output difference coefficient Scxs falls within the safety range [a, b], then relevant rotor status data information under corresponding wind speed conditions will be extracted and analyzed;

[0081] The setting method of the safety range [a, b] is as follows: obtain the power output difference coefficient Scxs under each wind speed condition, and combine the statistical algorithm to calculate the average power output difference coefficient and the standard deviation of the power output coefficient of variation σ, and according to the average power output coefficient of variation And the standard deviation of the power output difference coefficient σ, set the safety range Where k is a constant, usually ranging from 1 to 3, corresponding to different confidence levels, and the specific value is set by the user (according to actual conditions);

[0082] S33, statistically analyzing the relevant rotor state data information under the corresponding wind speed conditions extracted in S322 to construct a conditional data group, and analyzing and calculating the rotor kinetic energy Znn under the corresponding wind speed conditions based on the conditional data group, wherein the rotor kinetic energy Znn is specifically obtained in the following manner:

[0083]

[0084] Where m is the number of regions into which the rotor is divided, j = 1, 2, 3, ..., m, Zg j Expressed as the mass of the rotor in the jth region, Jz j It is represented as the distance of the jth region from the rotation axis, Jsd is represented as the angular velocity of the rotor, Expressed as rotor inertia, rotor inertia is a physical quantity that represents the rotor's resistance to changes in its rotation speed. The larger the inertia, the more difficult it is for the rotor to accelerate or decelerate quickly when rotating;

[0085] The distribution state of the mass Zg on each divided area of ​​the above-mentioned rotor can be monitored and obtained by strain gauges or vibration sensors. The strain gauges are used to monitor the stress and strain conditions on the wind wheel blades and other rotating parts, thereby reflecting the changes in the mass distribution of the rotor during rotation, which helps to detect mass imbalance or blade damage.

[0086] The distance Jz of each segmented area from the rotation axis can be periodically calibrated or monitored by a laser rangefinder or a visual sensing system; these devices can be used to detect whether the position of the blades or rotor has changed, ensuring that the wind wheel operates normally and maintains the designed geometric relationship.

[0087] The angular velocity Jsd of the rotor can be monitored by a speed sensor or an encoder to obtain the real-time angular velocity of the rotor (ie, the number of rotations of the rotor per minute).

[0088] The rotor kinetic energy Znn refers to the mechanical energy stored in the rotor due to its rotation. In a wind turbine, this energy comes from the wind energy captured by the wind wheel.

[0089] S34, statistically analyzing the rotor kinetic energy Znn under the corresponding wind speed conditions obtained in S33 to determine the range of rotor kinetic energy absorption under the wind speed conditions corresponding to the power output difference coefficient Scxs.

[0090] In this embodiment, firstly, by calculating the power output difference coefficient Scxs, the power output change under different wind speed conditions can be effectively analyzed. This difference coefficient reflects the degree of deviation between the actual power output and the average output power. According to this coefficient, the power fluctuation of the generator set under different wind speed conditions can be accurately evaluated, and the foundation for subsequent power smoothing optimization can be laid. Through this analysis, it is possible to effectively identify the situation where the power output fluctuation is large or unstable, so that the system's response to wind speed changes is more intelligent and dynamic. Secondly, based on the comparison and screening of the safety range, by comparing the power output difference coefficient Scxs with the preset safety range, the power fluctuation range that can be absorbed by the rotor kinetic energy under the corresponding wind speed conditions is screened out. This screening step ensures that the relevant rotor state data information is extracted and analyzed under reasonable and safe power output difference conditions, thereby avoiding invalid or excessive energy absorption adjustments under unstable or excessive fluctuations, and improving the stability and safety of the system. Then, through the calculation and analysis of the rotor kinetic energy, the present invention can accurately quantify the mechanical energy stored in the rotor under different wind speed conditions. The rotor kinetic energy is calculated based on the mass of each region of the rotor, the distance from the rotation axis, and the angular velocity and other parameters. In this way, by constructing a conditional data set and combining it with specific wind speed conditions, the system can accurately determine how much kinetic energy the rotor can absorb at a specific wind speed, thereby accurately controlling the acceleration and deceleration response of the rotor. This process not only optimizes the utilization of the rotor inertia, but also makes the response of the wind turbine smoother and more efficient when the wind speed fluctuates. Finally, through the statistical analysis of the rotor kinetic energy absorption range, the present invention can accurately determine the range of rotor kinetic energy absorption according to the power output difference under specific wind speed conditions. This statistical processing based on precise data not only ensures that the wind turbine can effectively absorb kinetic energy under wind speed fluctuations, but also further reduces the violent fluctuations in power output, and improves the stability of the power output of the generator set and the utilization rate of wind energy. In summary, this method can more efficiently and safely achieve power smoothing optimization of wind turbines through the calculation of the power output difference coefficient, the precise analysis and dynamic adjustment of the rotor kinetic energy, significantly reduce power fluctuations and improve system stability.

[0091] Example 4

[0092] Please refer to Figure 1 , specifically: S4 specific steps include:

[0093] S41, based on the preliminary screening of the matching range of rotor kinetic energy absorption, and combined with the method of obtaining the rotor kinetic energy Znn, to determine the range of the rotor angular velocity Jsd;

[0094] S42, according to the ratio of the speed of the tip of the wind rotor blade to the corresponding wind speed, calculate the tip speed ratio Jsb under different wind speed conditions, which is specifically obtained in the following manner:

[0095]

[0096] Where Bjz represents the radius of the wind wheel, Jsd represents the angular velocity of the rotor, and Fs represents the wind speed.

[0097] The radius Bjz of the wind wheel can be regularly calibrated by a laser rangefinder or a visual inspection system to check the wear or damage of the blades.

[0098] The wind speed Fs can be monitored and obtained through a wind speed sensor (common types include ultrasonic anemometers or mechanical anemometers);

[0099] The specific steps of S4 also include:

[0100] S43. Based on the range of the rotor angular velocity Jsd and in combination with the tip speed ratio Jsb under different wind speed conditions obtained in S42, obtain the range of the tip speed ratio Jsb.

[0101] In this embodiment, first, the determination of the rotor angular velocity range is based on the initially screened matching rotor kinetic energy absorption range, combined with the calculation method of the rotor kinetic energy, to determine the reasonable range of the rotor angular velocity. This process ensures that the system can reasonably absorb and buffer energy under different wind speed conditions by accurately matching the rotor kinetic energy and angular velocity, further avoiding excessively fast or too slow rotor responses, thereby achieving smoother power output control. Secondly, through the calculation of the tip speed ratio, the system can accurately evaluate the ratio of the tip speed of the wind rotor blade to the wind speed under different wind speed conditions. The calculation formula of the tip speed ratio is based on the relationship between the radius of the wind rotor, the angular velocity of the rotor and the wind speed, ensuring that the system can accurately measure the utilization efficiency of wind energy. This step optimizes the wind rotor power coefficient by dynamically adjusting the tip speed ratio, which helps to maximize the realization of wind energy conversion efficiency and improve the overall output performance of the generator set. Finally, the acquisition of the tip speed ratio range combines the range of the rotor angular velocity and the calculation results of the tip speed ratio under different wind speed conditions, and determines the tip speed ratio range that is suitable for a variety of wind speed conditions. Through this step, the system can automatically adjust the operating parameters of the wind turbine according to the wind speed change, ensuring that the generator set is always in a relatively good working state under different wind speed conditions, thereby achieving stable power output and reducing power fluctuations. Therefore, this method optimizes the operating state of the wind turbine generator set under different wind speed conditions by accurately determining the rotor angular velocity range and the tip speed ratio range. This method not only improves the utilization efficiency of wind energy and ensures the smooth operation of the system, but also significantly reduces power fluctuations and enhances the overall performance and stability of the wind turbine.

[0102] Example 5

[0103] Please refer to Figure 1 Specifically: S5 includes the following steps:

[0104] S51, based on the tip speed ratio Jsb range obtained in S43, monitoring the efficiency of the wind rotor in converting wind energy into mechanical energy under the corresponding wind speed conditions within the tip speed ratio Jsb range, so as to obtain relevant energy conversion data information, wherein the relevant energy conversion data information includes the mechanical power value P generated by the wind rotor under each wind speed condition mechanical and the wind energy P captured by the wind rotor wind .

[0105] The specific steps of S5 also include:

[0106] S52. Based on the relevant energy conversion data information, the wind rotor power coefficient Fgxs under the corresponding wind speed condition is calculated. The wind rotor power coefficient Fgxs under the corresponding wind speed condition is obtained in the following manner:

[0107]

[0108] Where P mechanical is the mechanical power value generated by the wind rotor, that is, the mechanical energy extracted by the wind rotor from the wind, P wind It is expressed as the wind energy captured by the wind rotor, that is, the wind energy swept by the wind rotor. Among them, π*Bjz 2 is the area swept by the wind wheel; ρ is the air density, usually 1.225kg / m 3 ; π is the circumference of a circle, and its value is approximately 3.14159;

[0109] The mechanical power value P generated by the above wind wheel is mechanical It can be monitored and obtained through torque sensors and speed sensors. The torque sensor is installed on the main shaft or gearbox to measure the torque generated by the wind wheel. The speed sensor is usually installed on the main shaft of the wind turbine generator set to obtain the mechanical power value through the torque generated by the wind wheel and the speed calculation.

[0110] S53. Based on the method of obtaining the wind rotor power coefficient Fgxs in S52, the wind rotor power coefficient Fgxs under each wind speed condition is calculated respectively. After feature extraction, the maximum value of the wind rotor power coefficient Fgxs is extracted, and the maximum value of the wind rotor power coefficient Fgxs is used as the standard conversion condition.

[0111] In this embodiment, first, the energy conversion efficiency monitoring within the tip speed ratio range is carried out by monitoring the tip speed ratio under different wind speed conditions. The system can obtain the efficiency of the wind wheel in converting wind energy into mechanical energy under different wind speeds. This not only provides detailed energy conversion data information, including the wind energy captured by the wind wheel and the mechanical power generated by the wind wheel, but also can evaluate the energy conversion efficiency of the wind wheel under different wind speed conditions in real time. This provides an accurate basis for subsequent optimization, so that the system can dynamically adjust the power output to improve the overall power generation efficiency. Secondly, the accurate calculation of the wind wheel power coefficient measures the efficiency of the wind wheel in extracting energy from the wind. By comparing the mechanical power generated by the wind wheel with the captured wind energy, it provides an accurate efficiency evaluation for the optimization of wind turbine power. Finally, the power coefficient feature is extracted and used as the standard conversion condition. The maximum value represents the relatively good energy conversion efficiency of the wind wheel. The system can dynamically adjust the operating state of the wind turbine based on this maximum value to ensure that the wind energy capture efficiency is always maintained in actual operation.

[0112] Example 6

[0113] Please refer to Figure 1 Specifically: S6 includes the following steps:

[0114] S61. Based on the standard conversion conditions, trace back the wind speed conditions corresponding to the standard conversion conditions, and trace back to the corresponding tip speed ratio Jsb according to the wind speed conditions, and extract the angular velocity Jsd of the rotor under the corresponding wind speed conditions from the range of the angular velocity Jsd of the rotor according to the tip speed ratio Jsb under the wind speed conditions, and adjust the angular velocity Jsd of the rotor in the wind turbine according to the value of the angular velocity Jsd of the rotor to smooth the output power of the wind turbine.

[0115] In this embodiment, firstly, the tracing of the standard conversion conditions ensures that the wind turbine can operate in a better working state under different wind speed conditions. By tracing the corresponding wind speed conditions based on the standard conversion conditions, the system can automatically identify the better tip speed ratio under the wind speed conditions, thereby providing an accurate reference basis for the control and adjustment of the wind turbine. This process enables the system to quickly identify the situation of wind speed changes and quickly make adjustments to avoid unstable power output caused by wind speed fluctuations. Secondly, the extraction and dynamic adjustment of the rotor angular velocity further optimize the operating state of the wind turbine. By extracting the rotor angular velocity under the corresponding wind speed conditions from the rotor angular velocity range based on the tip speed ratio, the system can accurately adjust the operating speed of the wind turbine to meet the requirements of different wind speeds. Based on the extracted rotor angular velocity value, the system can adjust the angular velocity of the wind turbine in real time to keep it within a better range, thereby achieving dynamic and smooth control of the wind turbine output power. In short, by adjusting the rotor angular velocity, the system can effectively reduce the impact of wind speed fluctuations on the power output of the generator set and achieve smoothing of power output. This smooth control not only improves the output stability of the wind turbine set, but also reduces the impact on the power grid, ensuring the continuity and stability of power supply.

[0116] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A power optimization method for a wind turbine generator set, characterized in that: The following steps are included: S1. Deploy several groups of monitoring equipment in the wind farm in advance, and use the monitoring equipment to monitor and record relevant power output data information and relevant rotor status data information in the wind turbine in real time; S2. Preprocessing the relevant power output data information and the relevant rotor status data information to generate a wind power operation data set, and using dimensionless technology to standardize the information in the wind power operation data set; S3. Based on the relevant power output data information, the power output difference coefficient Scxs under different wind speed conditions is analyzed and calculated, and the power output difference coefficient Scxs is compared and analyzed with the preset safety range [a, b] to preliminarily screen out the matching range of rotor kinetic energy absorption; S4. Based on the initially selected matching range of rotor kinetic energy absorption, determine the range of rotor angular velocity Jsd, and calculate the tip speed ratio Jsb under different wind speed conditions according to the ratio of the speed of the tip of the wind rotor blade to the corresponding wind speed, and obtain the tip speed ratio Jsb range in combination with the range of rotor angular velocity Jsd; S5. Based on the tip speed ratio Jsb range obtained in S4, monitor the efficiency of the wind rotor in converting wind energy into mechanical energy under the corresponding wind speed conditions within the tip speed ratio Jsb range to obtain relevant energy conversion data information, and calculate the wind rotor power coefficient Fgxs under the corresponding wind speed conditions based on the relevant energy conversion data information, and extract the standard conversion conditions through feature extraction; S6. Based on the standard conversion conditions, trace back and adjust the rotor angular velocity Jsd to the output power of the wind turbine.

2. The power optimization method of a wind turbine generator set according to claim 1, characterized in that: The specific steps of S1 include: S11. deploying several groups of monitoring equipment in the wind farm in advance, wherein the several groups of monitoring equipment include power sensors, strain gauges, laser rangefinders, rotation speed sensors, wind speed sensors, and torque sensors; S12, using the monitoring equipment in S11 to monitor and record relevant power output data information and relevant rotor status data information in the wind turbine in real time, wherein the relevant power output data information includes the output power value Scg under various wind speed conditions; The relevant rotor state data information includes the mass Zg of each divided area of ​​the rotor, the distance Jz of each divided area from the rotation axis, and the angular velocity Jsd of the rotor.

3. The power optimization method of a wind turbine generator set according to claim 2, characterized in that: The specific steps of S2 include: S21, pre-processing the relevant power output data information and the relevant rotor state data information to identify and remove abnormal values ​​in the relevant power output data information and the relevant rotor state data information, and using an interpolation method to fill in the missing data, and at the same time, time-aligning the relevant power output data information and the relevant rotor state data information, and finally generating a wind turbine operation data set; S22. By using dimensionless processing technology, the information in the wind turbine operating data set is converted into unitless data through dimensionless processing technology, and the dimensionless wind turbine operating data set is standardized so that the corresponding data values ​​are mapped to the interval [0,1].

4. The power optimization method of a wind turbine generator set according to claim 3, characterized in that: The specific steps of S3 include: S31. Based on the relevant power output data information, the power output difference coefficient Scxs under different wind speed conditions is analyzed and calculated, which is obtained in the following way: Where n represents the number of wind speed conditions monitored, i = 1, 2, 3, ..., n, Scg i It is expressed as the output power value under wind speed condition i, Scg avg Expressed as average output power value.

5. The power optimization method of a wind turbine generator set according to claim 3, characterized in that: The specific steps of S3 also include: S32, pre-set the safety range [a, b], and compare and analyze it with the power output difference coefficient Scxs under various wind speed conditions to preliminarily screen out the matching range of rotor kinetic energy absorption. The specific judgment content is as follows: S321, if the power output difference coefficient Scxs does not fall within the safety range [a, b], the relevant rotor status data information under the corresponding wind speed conditions will not be extracted and analyzed at this time; S322, if the power output difference coefficient Scxs falls within the safety range [a, b], then relevant rotor status data information under corresponding wind speed conditions will be extracted and analyzed; S33, statistically analyzing the relevant rotor state data information under the corresponding wind speed conditions extracted in S322 to construct a conditional data group, and analyzing and calculating the rotor kinetic energy Znn under the corresponding wind speed conditions based on the conditional data group, wherein the rotor kinetic energy Znn is specifically obtained in the following manner: Where m is the number of regions into which the rotor is divided, j = 1, 2, 3, ..., m, Zg j Expressed as the mass of the rotor in the jth region, Jz j It is represented as the distance of the jth region from the rotation axis, Jsd is represented as the angular velocity of the rotor, Expressed as rotor inertia; S34, statistically analyzing the rotor kinetic energy Znn under the corresponding wind speed conditions obtained in S33 to determine the range of rotor kinetic energy absorption under the wind speed conditions corresponding to the power output difference coefficient Scxs.

6. The power optimization method of a wind turbine generator set according to claim 5, characterized in that: The specific steps of S4 include: S41, based on the preliminary screening of the matching range of rotor kinetic energy absorption, and combined with the method of obtaining the rotor kinetic energy Znn, to determine the range of the rotor angular velocity Jsd; S42, according to the ratio of the speed of the tip of the wind rotor blade to the corresponding wind speed, calculate the tip speed ratio Jsb under different wind speed conditions, which is specifically obtained in the following manner: Where Bjz represents the radius of the wind wheel, Jsd represents the angular velocity of the rotor, and Fs represents the wind speed.

7. The power optimization method of a wind turbine generator set according to claim 6, characterized in that: The specific steps of S4 also include: S43. Based on the range of the rotor angular velocity Jsd and in combination with the tip speed ratio Jsb under different wind speed conditions obtained in S42, obtain the range of the tip speed ratio Jsb.

8. The power optimization method of a wind turbine generator set according to claim 7, characterized in that: The specific steps of S5 include: S51, based on the tip speed ratio Jsb range obtained in S43, monitoring the efficiency of the wind rotor in converting wind energy into mechanical energy under the corresponding wind speed conditions within the tip speed ratio Jsb range, so as to obtain relevant energy conversion data information, wherein the relevant energy conversion data information includes the mechanical power value P generated by the wind rotor under each wind speed condition mechanical and the wind energy P captured by the wind rotor wind .

9. The power optimization method of a wind turbine generator set according to claim 8, characterized in that: The specific steps of S5 also include: S52. Based on the relevant energy conversion data information, the wind rotor power coefficient Fgxs under the corresponding wind speed condition is calculated. The wind rotor power coefficient Fgxs under the corresponding wind speed condition is obtained in the following manner: Where P mechanical is the mechanical power value generated by the wind wheel, P wind Expressed as the wind energy captured by the wind rotor. Among them, π*Bjz 2 is the area swept by the wind wheel; ρ is the air density; π is the circumference of a circle; S53. Based on the method of obtaining the wind rotor power coefficient Fgxs in S52, the wind rotor power coefficient Fgxs under each wind speed condition is calculated respectively. After feature extraction, the maximum value of the wind rotor power coefficient Fgxs is extracted, and the maximum value of the wind rotor power coefficient Fgxs is used as the standard conversion condition.

10. The power optimization method of a wind turbine generator set according to claim 1, characterized in that: The specific steps of S6 include: S61. Based on the standard conversion conditions, trace back the wind speed conditions corresponding to the standard conversion conditions, and trace back to the corresponding tip speed ratio Jsb according to the wind speed conditions, and extract the angular velocity Jsd of the rotor under the corresponding wind speed conditions from the range of the angular velocity Jsd of the rotor according to the tip speed ratio Jsb under the wind speed conditions, and adjust the angular velocity Jsd of the rotor in the wind turbine according to the value of the angular velocity Jsd of the rotor to smooth the output power of the wind turbine.

Images